{"title":"Insights into component testing process","authors":"Vikrant S. Kaulgud, V. Sharma","doi":"10.1145/1985374.1985382","DOIUrl":null,"url":null,"abstract":"Effective component testing (or commonly termed as Unit Testing) is important to control defect slippage into the testing stage. Often testing teams lack in-process visibility into the effectiveness of ongoing component testing. Using project data such as code coverage and schedule and effort estimates, we generate temporal and rate-based insights into component testing effectiveness. A simple composite metric is used for measuring and forecasting the health of the component testing process. The early warning signals, based on the forecast and associated insights, lead teams to take proactive actions for improving component testing. In our ongoing experimental studies, we have observed that use of these insights cause a substantial reduction in defect slippage.","PeriodicalId":103819,"journal":{"name":"Workshop on Emerging Trends in Software Metrics","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Workshop on Emerging Trends in Software Metrics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1985374.1985382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
Effective component testing (or commonly termed as Unit Testing) is important to control defect slippage into the testing stage. Often testing teams lack in-process visibility into the effectiveness of ongoing component testing. Using project data such as code coverage and schedule and effort estimates, we generate temporal and rate-based insights into component testing effectiveness. A simple composite metric is used for measuring and forecasting the health of the component testing process. The early warning signals, based on the forecast and associated insights, lead teams to take proactive actions for improving component testing. In our ongoing experimental studies, we have observed that use of these insights cause a substantial reduction in defect slippage.